Triple

T15458128
Position Surface form Disambiguated ID Type / Status
Subject Eje Cafetero E371825 entity
Predicate transportHub P726 FINISHED
Object La Nubia Airport E838708 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: La Nubia Airport | Statement: [Eje Cafetero, transportHub, La Nubia Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Nubia Airport
Context triple: [Eje Cafetero, transportHub, La Nubia Airport]
  • A. La Nubia Airport chosen
    La Nubia Airport is a small regional airport serving the city of Manizales in Colombia’s coffee-growing region.
  • B. Abu Simbel Airport
    Abu Simbel Airport is a small regional airport in southern Egypt that serves tourists visiting the nearby Abu Simbel temples and surrounding area.
  • C. Kufra Airport
    Kufra Airport is a public airport serving the remote town of Al Kufrah in southeastern Libya, providing vital regional and domestic air connectivity.
  • D. Aswan International Airport
    Aswan International Airport is a regional airport in southern Egypt that serves the city of Aswan and nearby tourist destinations along the Nile.
  • E. El-Obeid Airport
    El-Obeid Airport is a public airport serving the city of El-Obeid and the surrounding region in central Sudan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f1623f0819086f6fc2bfd536609 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21b7b600819081a6087bd6309237 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:32 a.m.